The MaCAD is a unique online programme training a new generation of architects, engineers and designers ready to develop skills into the latest softwares, computational tools, BIM technologies and AI towards innovation for the Architecture, Engineering and Construction (AEC) industry.
The Re-Iterating Maze helps inmates at Alcatraz develop meditative practices through rehabilitation, using their sentence to make a more peaceful existence possible. Our concept allows prisoners a mindful form of exercise, allowing them to use their time outdoors exploring multidimensional pathways. Mindful walking encourages the brain to focus on the activity of traversing a determined path. By … Read more
Abstract Prisons are constrained by tangible realities – static physical forms, high-density layouts, lack of amenity and limited access to natural spaces. These constraints are typically a result of inflexible systems and rigid hierarchies with high oversight to keep prisoner behaviour in check, but result in the need for efficient use of space and cost-effectiveness. … Read more
Overview PaperLink WIP – This study specifically explores Physics-Informed Neural Networks (PINNs) and Computational Fluid Dynamics (CFD) to analyze pedestrian wind comfort. It aims to integrate these neural network models into a web application using Three.js and other tools. By utilizing data from OpenWeatherMap, and OpenStreetMap, the project aims to support real-time simulations and visualizations … Read more
Research Questions: Can climate sensitive facade interventions reduce the intensity of the Urban Heat Island effect within urban blocks in arid climates?“ Research Goal: The goal is to propose simplified, climate-sensitive facade interventions in highly urbanized cities that reduce energy loads by mitigating Urban Heat Island (UHI) effects, while complying with climate-resilient regulations. These interventions … Read more
A road map using Ai & computational design # 01 the road map To convert a 2D raster plan into a BIM model, we first need to recognize the image contents and convert them into vectors, attaching relevant data. So , Our process focuses on three stages: image-to-vector, vector-to-graph , and finally graph-to-BIM During our … Read more
Abstract This study examines the pressing problem of violence against women in Mexico City, focusing specifically on strategies to prevent the escalation of violence that can lead to femicides. The persistence of gender-based violence in the city is aggravated by socioeconomic disparities, inadequate urban planning, and a deficiency of safe public spaces. The notable increase … Read more
In a world driven by digital transformation, the realm of architecture and design faces new challenges in achieving flexibility, scalability, and efficiency. One of the most pressing issues is modular determination—how do we ensure that modular structures fit together seamlessly, across various design patterns? Design as Grammar addresses this by leveraging Graph Machine Learning (Graph … Read more
Introduction BIM and Cloud Adoption The construction industry is still experiencing a digital revolution led by the widespread adoption of Building Information Modeling (BIM) and cloud computing technologies. BIM has established itself as the central tool for the digital planning, construction and management of buildings, while cloud computing is transforming collaboration and data access. Studies … Read more
Table of contents Abstract Hypothesis Objective Overall process We start with a conceptual solid component, which is essentially a 3D representation of walls, slabs, doors, etc. We then classify the different components within the building. This helps us understand the boundary of spaces and the connection between them. Next, we extract the space massing from … Read more
Abstract As we advance into the 21st century, addressing the global housing crisis becomes imperative. By 2025, approximately 1.6 billion people will lack adequate housing, necessitating the construction of 96,000 affordable homes daily to meet the demand of 3 billion people by 2030 (Masterson, 2022). Urban areas, which now host over 50% of the world’s … Read more
City-Oriented Modeling for Observational Radiative Thermal comfort CONCEPT The idea behind C.O.M.F.O.R.T is to provide an effective tool for architects and urban planners to design cooler and more sustainable cities, leveraging the power of machine learning and AI technologies. FACTORS OF IMPACT To create COMFORT we had to study the different factors of impact which … Read more
Daylight autonomy is a climate-based metric that measures the percentage of occupied hours during which a given space receives a specific amount of light, typically 300 lux, through natural daylight alone. It is used to evaluate energy efficiency in building designs by evaluating how much artificial lighting can be reduced throughout the year (Lorenz et … Read more
Abstract Architectural drawings and construction documentation are critical in the construction industry, serving as the main means of communication between different disciplines and acts as a blueprint on guiding the construction of the built environment. However, errors in these drawings are quite common and often leads to significant delays, cost overruns, and structural issues. This … Read more
Vocal Commands for Autodesk Revit Problem Despite decades of technological advancement, the core user experience between man and computer has remained nearly unchanged. This tedious and repetitive process requires designers to spend extreme amounts of time that could be saved through updated methods. This thesis explores a potential future for computer user experience, utilizing AI … Read more
Thermal Insight would be a standalone app that optimizes indoor environments by predicting thermal comfort. With simulations from trained models to help enhance occupant comfort and energy efficiency, evaluating metrics like PMV, PPD, and MRT. This tool would help improve well-being and productivity while achieving efficiency goals. Abstract Methodology Use Case Data Analysis Results and … Read more
Project Aim In this project we aim to predict the type of vehicle crash that can be foreseen in the city of New York based on the traffic volume, using Graph Neural Networks (GNNs). To develop this machine learning model we use 3 different datasets. The model could hold potential if developed further, to be … Read more
